T. Vetter, A. Hurlbert, and T. Poggio. View-based models of 3D object recognition: invariance to imaging transformations. Cereb. Cortex, 3:261--269, 1995. Home/Search Document Not in Database Summary Related Articles Check |
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Quo vadis Face Recognition? - Gross, Shi, Cohn (Correct)
....approach using PCA as a probability density estimation tool. Li et al. 17] have developed a view based piece wise SVM model for face recognition. In the feature based approach, Cootes et al. 5] proposed a 3D active appearance model to explicitly compute the face pose variation. Vetter et at. [32, 31] learn a 3D geometry appearance model for face registration and matching. However, today the exact trade offs and limitation of these algorithms are relatively unknown. To evaluate the performance of these algorithms, Phillips et al. have conducted the FERET face algorithm tests [23] based on ....
Thomas Vetter, Anya Hurlbert, and Tomaso Poggio. View-based models of 3D object recognition: Invariance to imaging transformations. Cerebral Cortex, 5(3):261--269, 1995.
How Visual Cortex Recognizes Objects: The Tale of the.. - Riesenhuber, Poggio (2002) Self-citation (Poggio) (Correct)
....central topics concerning the neural mechanisms of object recognition. 4.1 Selectivity Invariance is only one requirement for object recognition, the other one being selectivity. Several studies have established that IT neurons can become tuned to task relevant objects and their full or partial [66] views [33, 10, 37] or to objects in the monkey s environment [2] suggesting that these neurons provide a representation of objects occuring in an animal s environment. The preferred stimuli of neurons in intermediate stages of the ventral stream are less clear, partly owing to the difficulty of ....
.... dictionary of complex features in PIT is affected by visual experience [33] Computationally, hard recognition tasks involving background and clutter require the selection of appropriate complex features, depending on the class of object (early simulations of feature selection used a HyperBF model [66] or [3] It will be important to investigate with computer experiments how feature sets could be learned using plausible cortical mechanisms and how they may affect object recognition, in particular object detection performance. In particular, learning effects may explain intriguing, recent data ....
T. Vetter, A. Hurlbert, and T. Poggio. View-based models of 3D object recognition: invariance to imaging transformations. Cereb. Cortex, 3:261--269, 1995.
Face Recognition From One Example View - Beymer, Poggio (1995) (50 citations) Self-citation (Poggio) (Correct)
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Thomas Vetter, Anya Hurlbert, and Tomaso Poggio. View-based models of 3D object recognition: Invariance to imaging transformations. Cerebral Cortex, 3:261--269, May/June 1995.
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